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Geometric model for vision-based door detection

机译:基于视觉的门检测的几何模型

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Emerging assistive technologies, such as assistive domotics and socially assistive robots have considerable potential for enhancing the lives of many elderly and physically challenged people throughout the world. Blind and visually impaired people can use these technologies for many tasks recognizing objects, handling various household duties, navigation in indoor and outdoor environments. Door detection is one of the important issues in indoor navigation. This paper presents a novel vision-based door detection technique. It is based on the geometric properties of the 4-side polygon. The efficacy of the proposed method is tested using large database of images with different levels of complexity. The experimental results show the robustness of the proposed method against changes in colors, sizes, shapes, orientations, and textures of the door. Detection rate of 83% with relatively low false positive rate for simple images is achieved. This proposed algorithm is suitable for real-time, portable applications where it only requires one digital camera and low computational resources.
机译:新兴的辅助技术,如辅助宗旨和社会辅助机器人具有相当大的潜力,可以增强全球许多老人和身体挑战人士的生活。盲人和视力受损人们可以为许多任务使用这些技术来识别对象,处理各种家务职责,室内和室外环境中的导航。门检测是室内导航中的重要问题之一。本文提出了一种新型视觉的门检测技术。它基于4侧多边形的几何特性。使用具有不同级别的复杂程度的图像进行大量图像测试所提出的方法的功效。实验结果表明,所提出的方法对门的颜色,尺寸,形状,方向和纹理的变化的鲁棒性。达到了简单图像的相对较低的假阳性率的83%的检出率为83%。该提议的算法适用于实时,便携式应用,其中仅需要一个数码相机和低计算资源。

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